We extract SMB profiles, contact details, NAICS/SIC classifications, and operating hours from Manta. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Business Profiles objects from manta.com. All fields typed and schema-versioned.
"manta_url": "https://www.manta.com/c/mk2q3r1/apex-plumbing", "business_name": "Apex Plumbing Services", "year_established": 1998, "claimed_status": true, "primary_category": "Plumbing Contractors", "verification_status": "Verified"
| # | manta_url | business_name | about_text | year_established | claimed_status | logo_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Firmographics objects from manta.com. All fields typed and schema-versioned.
"manta_url": "https://www.manta.com/c/mk2q3r1/apex-plumbing", "employee_count": "10 to 19", "revenue_estimate": "$1M to $2.5M", "ownership_type": "Private", "naics_code": "238220", "sic_code": "1711"
| # | manta_url | employee_count | revenue_estimate | ownership_type | naics_code | naics_description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Contact & Social objects from manta.com. All fields typed and schema-versioned.
"manta_url": "https://www.manta.com/c/mk2q3r1/apex-plumbing", "phone_primary": "(555) 234-5678", "website_url": "http://www.apexplumbing.example.com", "facebook_url": "https://facebook.com/apexplumbing", "contact_person_name": "John Doe", "contact_person_title": "Owner"
| # | manta_url | phone_primary | phone_alt | website_url | email_address | facebook_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from manta.com. All fields typed and schema-versioned.
"review_id": "rev_984123", "manta_url": "https://www.manta.com/c/mk2q3r1/apex-plumbing", "star_rating": 4.5, "review_date": "2025-11-12", "review_text": "Arrived on time and fixed the leak quickly.", "author_name": "Sarah Jenkins"
| # | review_id | manta_url | author_name | star_rating | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location & Operations objects from manta.com. All fields typed and schema-versioned.
"manta_url": "https://www.manta.com/c/mk2q3r1/apex-plumbing", "street_address": "123 Main St", "city": "Austin", "state": "TX", "zip_code": "78701", "latitude": 30.2672, "longitude": -97.7431
| # | manta_url | street_address | city | state | zip_code | latitude |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Manta scraper navigates complex directory taxonomies, handles pagination limits, and circumvents anti-bot measures to deliver normalised firmographic records.
Capture business name, description, year established, and claimed status directly from Manta company pages.
Extract employee count brackets, revenue estimates, ownership type, and exact NAICS/SIC classifications.
Scrape primary phone numbers, alternative contacts, external website links, and associated social media profiles.
Compile star ratings, review text, author details, and owner responses across business listings.
Normalise street addresses, cities, states, and zip codes alongside operating hours and payment methods.
Systematically crawl through Manta industry categories and sub-categories to build exhaustive regional lists.
Identify new business registrations, updated contact details, or newly claimed profiles without full re-crawls.
Bypass Cloudflare and rate limits using residential proxy rotation and human-like request pacing.
Clean messy user-submitted data, standardise phone formats, and structure addresses into queryable fields.
Brief in. Clean data out.
Provide target states, cities, or industry categories. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and category traversal logic for manta.com.
Schema validation, null-rate checks, deduplication, and sample data review before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from broad business directories requires systematic traversal and strict normalisation. Here is how we maintain pipeline integrity.
Manta organizes millions of records through a nested hierarchy of locations and industries. We map this taxonomy completely, ensuring no sub-category or remote city is missed during the extraction phase.
Directory search results often cap at 1,000 visible records regardless of total matches. Our pipeline injects granular filters (by zip code or micro-category) to force result sets under the limit, ensuring 100% data capture.
SMB directories contain highly variable data formatting. We apply strict regex and validation rules to normalise phone numbers, parse addresses into distinct components, and map proprietary categories to standard NAICS codes.
Aggressive crawling triggers IP bans and CAPTCHA walls. We route requests through US-based residential ISP proxies with realistic browser fingerprints to maintain high concurrency without interruption.
Businesses often have multiple unclaimed profiles on Manta. We use deterministic hashing on name and address fields to flag duplicates, delivering a clean, unique dataset to your warehouse.
Sales teams extract newly listed or claimed businesses in specific regions to build targeted outbound contact lists.
Revenue operations teams cross-reference existing CRM accounts with Manta firmographics to fill missing revenue or employee data.
Marketing agencies monitor citation consistency (Name, Address, Phone) across Manta and other directories for their clients.
Analysts aggregate NAICS codes and geographic density to identify growing industry hubs and regional market saturation.
Franchises track competitor locations, operating hours, and review sentiment across specific metropolitan areas.
Private equity firms monitor SMB growth signals, category expansion, and regional business formation trends.
"Manta houses millions of fragmented SMB records across thousands of local categories. Extracting this requires systematic directory traversal, not just simple URL lists."
Scraping business directories introduces unique challenges: infinite pagination loops, aggressive rate limiting, and highly variable DOM structures. DataFlirt manages the proxy rotation and schema normalisation so you receive clean, deduplicated firmographic data ready for your CRM or data warehouse.
Everything supported by our manta.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles broad directory crawling and deduplication. Playwright executes JavaScript required for obfuscated contact details and dynamic UI elements.
We maintain US-specific residential ISP proxy pools. Rotation happens per-request to bypass rate limits while maintaining high throughput across millions of pages.
Pipelines run on AWS Lambda and Kubernetes. Airflow handles complex category traversal dependencies and SLA alerting, with state managed in PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About manta.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available firmographic information from Manta is generally permissible. DataFlirt targets only public, non-authenticated business profiles, contact details, and reviews. We do not extract private user data or circumvent authentication walls. Clients should review Manta's ToS and consult legal counsel for specific use cases.
Manta limits visible search results for broad queries. We bypass this by injecting granular parameters — combining micro-categories with specific zip codes — to force the result sets below the display cap, ensuring complete extraction.
Yes. User-submitted directory data is notoriously inconsistent. Our pipeline applies post-processing regex and validation rules to standardise phone formats and split raw address strings into discrete street, city, state, and zip fields.
For targeted regional or category lists, we can configure daily or weekly refresh pipelines. Full directory sweeps spanning millions of records are typically executed on a monthly or quarterly cadence depending on your requirements.
Yes. Where Manta displays industry classifications, we extract both the numerical codes and the associated textual descriptions, mapping them cleanly to your database schema.
Our smallest packages start at defined category or state-level extracts (typically 50,000-100,000 records). For nationwide directory sweeps, we price based on compute volume and delivery frequency. Contact us for a scoped quote.
Absolutely. We provide a sample run of up to 1,000 business profiles as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of regional contractors or a continuous feed of newly registered SMBs — we scope, build, and operate the pipeline. Tell us what you need.
